The proposed research applies cognitive engineering methods to understand and support complex, cognition and work activities within the acute care environment, using emergency medicine as the research setting. The research will provide a fundamental and comprehensive picture of work domain complexities and challenging sensemaking, decision-making, and planning/replanning tasks; along with the individual and team expertise required to meet those challenges. The research uses emergency medicine as a field laboratory because it both explicates some of the most challenging conditions for cognitive work - high risk, time-pressure, and uncertainty - and therefore provides a strong opportunity to generalize findings to other complex health care environments; while at the same time providing an environment which can clearly benefit from the decision aids, visualizations, and other supportive technologies that can result from cognitive engineering analyses. This project utilizes the extensive prior experience of research team in human factors and cognitive engineering analyses of health care work (including emergency medicine) and other high risk work environments; and evaluating the usability and effectiveness of information displays and decision support technologies designed to support complex, cognitive work. The application addresses the fundamental, research nature of the call for applications by including a comprehensive cognitive engineering analysis of emergency medicine along with targeted development and evaluation of visualizations, decision- support, and other aiding solutions. Contributions from this research will include a fundamental understanding of the nature of cognition and clinical work in a high intensity medical environment - including both work related complexities, and practitioner expertise, knowledge, and skills - which can provided a basis for the design of health IT solutions which support clinical work and improve the effectiveness of medical care. Additionally, the research will develop and evaluate exemplar solutions for a targeted set of needs identified through the cognitive engineering analysis, thus providing a methodological example and proof-of-concept for translating cognitive engineering analyses into designs.